Toward basic understanding of the partition coefficient log P and its application in QSAR

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Pharmacology

Background:

• Log P is a key descriptor for molecular hydrophobicity in Quantitative Structure-Activity Relationship (QSAR) studies.
• Understanding the physical chemistry of partitioning phenomena remains challenging.
• Molecular hydrophobicity is critical for drug-receptor interactions, particularly with Cytochrome P450 enzymes.

Purpose of the Study:

• To develop a predictive model for log P based on physical chemical properties.
• To investigate the role of molecular hydrophobicity in ligand-Cytochrome P450 (CYP) interactions.
• To analyze the binding affinity of azole compounds with CYP2B and CYP3A enzymes.

Main Methods:

• Formulation of a simple predictive model for log P using solvent accessible surface area and solvation energy.
• Application of the log P descriptor in QSAR analyses of ligand-CYP interactions.
• Utilizing a bilinear model to correlate binding affinity with log P for azole compounds.

Main Results:

• A straightforward model was developed to predict log P.
• The binding affinity of 18 azole compounds with CYP2B and CYP3A was effectively described by a bilinear model of log P.
• Molecular hydrophobicity was identified as a significant factor influencing binding affinity.

Conclusions:

• The developed model provides insights into predicting and understanding log P.
• Molecular hydrophobicity plays a substantial role in the binding affinity of azole antifungals to CYP enzymes.
• The findings contribute to understanding the binding mechanisms in ligand-CYP interactions.